Tom Chittenden is Chief Data Science Officer and Founding Director of the Genuity Science Advanced Artificial Intelligence Research Laboratory. Tom is responsible for development and execution of our global AI/ML R&D strategy. This R&D initiative includes development of advance deep learning, statistical machine learning, and probabilistic programming analytics aimed at furthering scientific understanding of human disease initiation and progression, knowledge that can be directly applied in innovative products for better care and medicine in a range of disease areas.

The principal focus of the work of Tom and his team is the development and application of integrated systems biology models to investigate evolutionary factors of human disease. The broad objective is to understand how genetic variation and somatic mutation regulate aberrant gene activity and subsequent disease biology. To this end, Tom spent a year as a Visiting Research Scientist in the Department of Statistics at the University of Oxford, where he formulated a general strategy for constructing machine learning models by integrating a priori biological knowledge with multiple types of high-throughput genomic and phenotype data.

Tom’s work has been published in top-tier scientific journals, including featured articles in Nature and Science. In 2019, he was named among the top 100 A.I. Leaders in Drug Discovery and Advanced Healthcare by Deep Knowledge Analytics. He is regarded as one of the world’s leading authorities on A.I. and causal statistical machine learning in precision medicine.

Tom is an Accredited Professional Statistician™ with the American Statistical Association. In addition to his position at Genuity Science, he holds academic faculty appointments at Boston Children’s Hospital and the Harvard Medical School (HMS), where he lectures on biostatistics and mathematical biology. From 2016 to 2018, Tom held a Visiting Lecturer appointment in the Department of Biological Engineering at the Massachusetts Institute of Technology. He currently serves as a Senior Consultant for the HMS Research Computing Group. He is a Senior Fellow and Chief Statistical Sciences Advisor for the Global Strategic Initiatives and Planning Committee of the International Society for Philosophical Enquiry.

Tom holds a PhD in Molecular Cell Biology and Biotechnology from Virginia Tech and a DPhil in Computational Statistics from the University of Oxford. His multidisciplinary postdoctoral training includes experimental investigations in Molecular and Cellular Cardiology from the Dartmouth Medical School and Integrative Functional Genomics, Biostatistics, and Mathematical Biology from the Dana-Farber Cancer Institute and the Harvard School of Public Health.